3 дня назад
Research Engineer, Data Infrastructure (AI)
200 000 - 350 000$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Engineer, Data Infrastructure (AI): Building scalable data infrastructure and high-throughput pipelines for acquiring, processing, filtering, deduplicating, and augmenting massive datasets used to pretrain foundational models, with an accent on dataset quality, reproducibility, and data-mixture optimization. Focus on designing ablation experiments, co-designing data versioning and loading systems with research teams, and managing novel external data sources.
Location: On-site in San Francisco, California. also has in-person offices in London and Bangalore. Visa sponsorship support is available on a case-by-case basis.
Salary: $200,000–$350,000 per year, plus equity.
Company
develops AI model architectures and experiences that enable foundation models to learn from and interact with the world like humans.
What you will do
- Build and operate scalable infrastructure for acquiring, ingesting, and combining massive text datasets.
- Design reproducible high-throughput pipelines for preprocessing, filtering, deduplication, and data augmentation.
- Run ablation experiments to evaluate how data sources, processing choices, and mixture weights affect model quality.
- Partner with research and infrastructure teams on data loading, versioning, and experimentation systems.
- Establish data-quality standards and connect dataset characteristics with model behavior.
- Source novel datasets and manage relationships and budgets with external data vendors and partners.
Requirements
- Hands-on experience with ML data infrastructure, including training data pipelines, dataset versioning, large-scale data loading, and connections between data systems and model training and inference.
- Strong software engineering skills, including clean, well-tested code and fluency with modern tools.
- Experience building and evaluating datasets for generative models and working knowledge of model training and inference.
- Experience with large-scale parallel data processing using tools such as Ray, Spark, or Kubernetes.
- Experience with language model pretraining.
- Ability to work in person from the San Francisco office.
Culture & Benefits
- In-person, collaborative work environment with a focus on rapid execution and high-quality engineering.
- Fully covered medical, dental, and vision insurance for employees and families.
- 401(k), flexible PTO, and parental leave.
- Monthly commuter allowance and daily lunch, dinner, and snacks.
- Competitive base salary and equity package.
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